In many signal processing applications a digitizing tablet is used to convert pen or stylus motion into a set of electrical data which is then processed by digital equipment. Typically, there is a special electronic or electromagnetic grid or surface which detects the X and Y positions of the pen as it moves along the surface at a periodic rate. The information is present as two digital data words at a periodic clock rate. This class of technology is used for signature verifications, automatic drafting, graphics, character recognition, handwriting recognition and so forth. In each case, the user writes on the writing surface with the writing instrument and the position is monitored electronically.
In connecting such a device directly to a processing system there are problems because the raw data may contain certain kinds of noise or other defects which can adversely effect applications that process the data for editing, character recognition, graphics and other uses. The noise may be electrical or mechanical noise produces by the equipment employed to generate the sequence of signals corresponding to the stroke of the writing instrument. The noise may also be nature noise produced by the writer retracing a portion of the stroke at either end.
An angle filter used in stroke recognition produces output at a given angle. There are a number of patents dealing with this technological area, each having certain advantages and disadvantages.
In U.S. Pat. No. 4,718,103 to Shojima et al. a method and apparatus are described for on-line recognizing handwritten patterns. A handwritten pattern approximated to a series of polygonal lines consisting of segments is compared with a candidate pattern selected from dictionary patterns stored in the memory, basing on the angular variation between angular variations of adjoining segments of both patterns is outside of a certain range, it is tested whether the difference between an angular variation across three or more consecutive segments and the above reference angular variation is within the range.
In U.S. Pat. No. 4,653,107 to Shojima et al. coordinates of a handwritten pattern drawn on a tablet are sequentially sampled by a pattern recognition unit to prepare pattern coordinate data. Based on an area encircled by segments created by the sampled pattern coordinate data of one stroke and a line connecting a start point and an end point of the one-stroke coordinate data, the sampled pattern coordinate data of the one stroke is converted to a straight line and/or curved line segments. The converted segments are quantized and normalized. The segments of the normalized input pattern are rearranged so that the input pattern is drawn in a predetermined sequence. Differences between direction angles for the rearranged segments are calculated. Those differences are compared with differences of the direction angles of the dictionary patterns read from a memory to calculate a difference therebetween. The matching of the input pattern and the dictionary pattern is determined in accordance with the difference. If the matching fails, the first or last inputted segment of the input pattern is deleted or the sampled pattern coordinate data of the next stroke is added, to continue the recognition process.
In U.S. Pat. No. 4,731,857 to Tappert a method of processing a word is set forth, with the segmentation and recognition steps combined into an overall scheme. This is accomplished by a three step procedure. First, potential or trail segmentation points are derived. This is done in a manner so as to ensure that essentially all true segmentation points are present but also includes extra or not true segmentation points. Second, all combinations of the segments that could reasonably be a character are sent to a character recognizer to obtain ranked choices and corresponding scores. Finally, the recognition results are sorted and combined so that the character sequences having the best cumulative scores are obtained as the best word choices. For a particular word choice there is a corresponding character segmentation, simply the segment combinations that resulted in the chosen characters. With this recognition scheme the initial character segmentation is not final and need not be highly accurate, but is subject to a lesser constraint of containing the true segmentation points.
In Japanese Patent 57-159385 to Gijutsuin et al. sets forth a pattern reading system to enable highly accurate correlation, to cope with irregular local variation of handwritten letters etc. and to read complicated letter patterns by correlating characteristics extracted from an input pattern successively form general to details. The directional property of a line is extracted by a preparation section A from an object input pattern is accordance with information of a point and points around it. Using the extracted directional property pattern, higher order characteristics by directional projection of large area and lower order characteristics by directional projection of smaller area are extracted by a characteristic extraction section B. Further, matching between input pattern and mask for conception to be classified is made by a matching section C. The degree of matching is measured by correlation of higher order characteristics using the higher order characteristics provided beforehand and input pattern. Then, characteristic point is shifted in accordance with the result of correlation in higher order, and correlation and valuation of lower order characteristics are made. Thus, irregular letter patterns are read correctly.
In Japanese Patent 60-59486 to Kogyko et al a handwritten character is recognized by selecting a segment having a lower degree of difference among the segments of the other (one) side for either one of an input and a standard pattern as the lst (2nd) segment correspondence group and obtaining the degree of the difference among the groups which share 1 or more segments within both groups. A standard pattern S approximated by a broken line and an input pattern S' are normalized according to the size and positions of centroids and superposed to obtain the degree of the difference of the segments between both patterns. The segment having the lower degree of the difference is obtained, and plural groups are formed in paired forms, i.e., the 1st group l.sub.1 :l.sub.1 ' and the 2nd group l.sub.2, l.sub.3 :l.sub.2 ', l.sub.3 ', l.sub.4 ' respectively. Then l.sub.4 :l.sub.5 ', l.sub.6 ' is finally obtained. The degree of difference is detected for each group. Then the sum total of these degrees of difference is defined as the degree of difference between both patterns. This method is applied also to other standard patterns to decide an input pattern approximating a standard pattern. Thus the characters are recognized.
In U.S. Pat. No. 4,608,658 to J. Ward a method and apparatus are described for processing a series of digital signals representing a stroke of a stylus on a tablet to remove signals at the ends of the stroke caused by retracing, the series of signals corresponding to the X and Y coordinates of a series of points along the direction of travel of the stroke. The signals for each point in the series are compared to the signals of the points adjacent to it to form a second series of signals which contain only those signals corresponding to points having an ordinate value of its adjacent points. The first three points in the second series of signals are then processed to determine the ration of the distance from the first point to the second point to the distance from the second point to the third point and to determine the size of the angle formed by the three points. The distance ration is fed into a table-look-up which outputs a reference angle signal which is compared to the processed angle signal. If the processed angle signal is less than the reference angle, the second point in the second series is used as the end point and all points in the first series before that point are discarded as being caused by retracing. In the processed angle is equal to or greater than the reference angle. The first point in the second series is used as the end point. The last three points in the second series are processed in a similar manner to determine the correct end point. The last three points in the second series are processed in a similar manner to determine the correct end point. The last three points in the second series are processed in a similar manner to determine the correct point at the finish of the stroke. If the second series of signals consists of only two points further processing is not performed since each one of the two points is an end point of the stroke.
According to the present invention, a multi-scale recognizer measures distance between the first and last points in a stroke, and the lengths of each line segment to recognize the stroke.